CN113782130A - Genomics data management and diagnosis and treatment system and method - Google Patents
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Abstract
The invention discloses a genomics data management and diagnosis and treatment system, which solves the problems that only digital pathological files can be screened and diagnosis and treatment cannot be realized in the prior art, and comprises an information input module, a database module, a data management module and a medication auxiliary recommendation system; the information input module comprises a display module and a data transmission module, the data management module comprises a data updating unit and a data calling unit, and the medication auxiliary recommendation system comprises a gene combination prediction unit and a medication and gene test unit. Also provides a method for genomics data management and diagnosis and treatment. The data management technology is combined with the diagnosis and treatment technology, and starting from the genomics of cancer cells, the medicine prediction can be carried out on the disease diagnosis and treatment which is difficult to realize manually, and the relocation and the combined medicine screening of the known medicine can be carried out.
Description
Technical Field
The invention relates to the technical field of medical treatment and artificial intelligence, in particular to a genomics data management and diagnosis and treatment system and method.
Background
Medical machine technology plays a significant role in modern medicine, and is one of the most interesting directions in the development process of science and technology. With the rapid development of artificial intelligence technology, machine technology is also widely and deeply researched and applied in the medical field, and artificial intelligence assisted medical treatment has become an emerging field in medicine. Pathological diagnosis is the standard for determining cancer cells at present, and pathological diagnosis is mainly made by observing pathological changes by a pathologist after pathological section, hematoxylin-eosin (H & E) staining and microscopic imaging, so that guidance opinions are provided for clinical diagnosis and treatment. However, with the improvement of medical image diagnosis level and the popularization and promotion of early cancer screening, the discovery rate of various tumors in the population is remarkably increased in recent years, the workload of pathological diagnosis is increased day by day, and the efficient and accurate development of pathological diagnosis faces a serious challenge.
Therefore, at present, most of the medical aids adopt artificial intelligence means to assist medical treatment and carry out pathological diagnosis. For example, the patent office 2020, 2.7 discloses an invention named as an artificial intelligence assisted pathological diagnosis system, and the publication number of the invention is CN 110767312A. The invention includes a pathology information base, a pathology expert base, and one or more programs executed by a processor, the programs including instructions for performing the steps of: receiving a digital pathology file; matching an intelligent diagnosis algorithm model for the digital pathological file to generate a preliminary diagnosis opinion and a preliminary analysis report; and when the preliminary diagnosis opinion is negative, taking the preliminary analysis report as a final analysis report, otherwise, entering a shunting procedure, matching a corresponding specialist and receiving the final analysis report from the specialist. The application also provides an artificial intelligence auxiliary pathological diagnosis method. The digital pathological file screening method and the digital pathological file screening device have the advantages that the preliminary screening of the digital pathological files is achieved by means of artificial intelligence, the screening is negative, the digital pathological files directly generate a preliminary analysis report, the screening possibly problematic digital pathological files are transferred to a special doctor for manual diagnosis, and accordingly workload of the pathological doctor is reduced. However, the invention can only screen digital pathological files, and cannot accurately judge human diseases and give diagnosis and treatment methods.
Disclosure of Invention
The invention aims to overcome the problems in the prior art and provides a genomics data management and diagnosis and treatment system and method, which combine the data management technology with the diagnosis and treatment technology, can start from the genomics of cancer cells according to the information input by a user, can predict the drugs for disease diagnosis and treatment which are difficult to realize manually, and can perform relocation and combined drug screening of the known drugs.
In order to achieve the purpose, the invention adopts the following technical scheme: the method comprises the following steps:
an information input module: for inputting cancer genomics data for a patient;
a database module: storing genomic data of common subtypes of various cancers;
a data management module: calling corresponding genomics data and a medicine combination prediction result according to the input patient information;
the medication auxiliary recommendation system comprises: according to the comparison between the called data and the patient data, the accurate medication assistance is carried out on the patient;
the medication auxiliary recommendation system comprises:
a gene combination prediction unit: predicting the individualization of cancer driver genes and drug combinations;
drug and gene test unit: the method can predict new anticancer indications of targeted drugs and small molecule drugs, and can realize relocation and combined drug screening of known drugs.
The database module is respectively connected with the data management module and the information input module, the information input module is connected with the gene combination prediction unit, and the genome and prediction unit and the drug and gene test unit are connected. The database module stores gene data of various cancers and various subtypes and individualized prediction results of cancer driving genes and medicine combinations, and the data management module manages information stored in the database module. When diagnosis and treatment are carried out, firstly, cancer gene information and cancer subtypes of a patient are input into the system through the information input module, the data management module retrieves data of corresponding subtypes from the database module according to the input information, the medication auxiliary recommendation system carries out medicine diagnosis and treatment prediction on the input cancer genes of the patient to be detected according to the stored prediction results of the corresponding subtypes, and new indication prediction is carried out, relocation and combined medication screening aiming at known medicines of individuals are carried out, and an optimal diagnosis and treatment scheme is given.
Preferably, the information input module includes:
a display module: the system is used for inputting patient identity information and displaying database information;
a data transmission module: patient cancer genomics data is retrieved from the medical system based on the patient entered identity information.
The information input module can input information through a touch display screen in the display module and can also input information through keys, and the display module can also be a card swiping device. When the system is used in a networking system, only the identity information of a patient needs to be input, the data transmission module can directly transmit the patient information in the medical system to the system, then the display module can display the cancer type and the cancer subtype of the patient, and after prediction, the diagnosis and treatment scheme of the patient given by the medication auxiliary recommendation system can be displayed, so that the system is convenient and quick.
Preferably, the data management module includes:
a data update unit: updating genomics data in the database module in real time;
a data calling unit: and calling genomics data of corresponding subtypes in the database module according to the content of the information input module.
The data updating unit and the data calling unit are both connected with the database module, and when new patient information is input, the information of the patient is stored in the database after diagnosis and treatment are finished.
Preferably, the gene combination prediction unit comprises a modeling module, wherein the modeling module is used for inputting genomics data and drug combinations, outputting corresponding treatment effects, and training to obtain the cancer diagnosis and treatment prediction model. The system also comprises a parameter optimization unit used for carrying out parameter optimization on the established multiple models. And selecting a medicine combination with a treatment effect as an optimal diagnosis and treatment scheme of the subtype through the established model. After patient information is input, according to the optimal drug combination sequence in the model, the new anticancer indications of the cancer driving genes of the patient to the targeted drugs and the small molecule drugs are predicted, and the individual diagnosis and treatment scheme is established by repositioning and combined drug screening of the known drugs.
A genomics data management and diagnosis and treatment method comprises the following steps:
s1: respectively collecting cancer genomics data of various cancers, and establishing a cancer genomics database;
s2: constructing a sample space of a whole genome according to data in a database;
s3: constructing an individual accurate medication auxiliary recommendation system facing a patient by utilizing artificial intelligence and a bioinformatics algorithm based on genomics data;
s4: establishing a data management module for searching, inquiring and authority management control of genomics data;
s5: the information of the patient is input into the medication auxiliary recommendation system, and the medication auxiliary system performs combined medication screening according to the gene condition of the patient.
Individual data is collected for each cancer type, cancer subtypes are classified according to the cancer type and the tissue they control, and prediction of drug targets is then performed according to the specifically distinguished cancer subtype and the tissue it controls. The invention predicts the individuation of cancer driving genes and medicine combination by constructing an individualized accurate medication auxiliary recommendation system for cancer patients, further predicts the new anticancer indications of approved targeted drugs and small molecular drugs, and performs relocation and combined drug screening of known drugs. And a data management module is arranged, so that the safety of gene data is ensured.
Preferably, the step S1 is further expressed as: aiming at a certain cancer, the genomics of the cancer patient is collected from various large medical institutions, and a cancer genomics data group covering the common subtype of the cancer is established; and storing a plurality of cancer genomics data groups together to construct a cancer genomics database. The database comprises a plurality of groups of cancer genomics data, each cancer is a category, each cancer category comprises a plurality of subtypes of the cancer, and each subtype also comprises genomics information of the subtype. Cancer is a malignant tumor derived from epithelial cells, which can be clinically assigned a corresponding type, i.e., a subtype of cancer. Different subtypes are sensitive to treatment to different degrees, and thus the treatment modalities used are different. According to the classification of the subtype, a corresponding genomics data set is established, which is beneficial to the targeted research of the people.
Preferably, the sample space in step S2 includes a sample space of the whole genome of the patient with each cancer and a sample space of the whole genome of the normal cells, and the sample space of the normal cells is used as a control group. The sample space contains control gene data corresponding to the patient's cancer genomic data, which is useful for predicting individual cancer types or drug targets for the interaction between cancer genes and genes.
Preferably, in step S3, the specific steps of constructing the patient-oriented individualized precision medication auxiliary recommendation system by using artificial intelligence and bioinformatics algorithm are as follows:
s3.1: classifying different subtypes of the cancer by genetic classification algorithm through gene network analysis;
s3.2: predicting a drug target based on the differentiated cancer types and tissues controlled thereby;
s3.3: and constructing a cancer diagnosis and treatment prediction model by using a random forest algorithm.
The genetic classification algorithm is an existing algorithm, and utilizes the genetic classification algorithm to perform differential expression gene classification on different cancers through gene network analysis on collected genomics data. Classifying and selecting the required genes by utilizing a plurality of SVM (support vector machines) based on a classifier; the information shared between genes and the information of co-expression are counted and analyzed by an algorithm. Gene expression patterns are classified according to the type of cancer and the tissue it controls, and prediction of drug targets is then performed according to the particular differentiated type of cancer and the tissue it controls. And finally, constructing a cancer diagnosis and treatment prediction model by using a random forest algorithm.
Preferably, the step S5 is further expressed as: the cancer genomics information of a patient is input into a medication auxiliary recommendation system, then the cancer type and the subtype are selected, a data management module updates a database, the medication auxiliary recommendation system carries out individualized diagnosis according to the common medication mode of the subtype, and the individual is subjected to prediction of new anticancer indications of targeted drugs and small molecular drugs, relocation of the known drugs and combined medication screening. The method can predict the medicine for disease diagnosis and treatment which are difficult to realize artificially, and carry out relocation and combined medicine screening of the known medicine aiming at individuals.
Therefore, the invention has the following beneficial effects: 1. individual prediction of cancer driving genes and drug combinations is carried out, and new anticancer indications of targeted drugs and small molecule drugs are further predicted; 2. the working efficiency of medical staff is improved, the proportion of the medical staff is simplified, and the operating cost of the hospital is reduced; 3. the method can predict the medicine for disease diagnosis and treatment which are difficult to realize artificially, and carry out relocation and combined medicine screening of the known medicine aiming at individuals.
Drawings
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a flow chart of the operation of the method of the present invention;
in the figure: 1. an information input module; 2. a database module; 3. a data management module; 4. a medication aid recommendation system; 5. a gene combination prediction unit; 6. drug and gene test units; 7. a display module; 8. a data transmission module; 9. a data update unit; 10. and a data calling unit.
Detailed Description
The invention is described in further detail below with reference to the following detailed description and accompanying drawings:
as shown in fig. 1, the present embodiment is a genomics data management and diagnosis and treatment system, which includes an information input module 1, a database module 2, a data management module 3, and a medication auxiliary recommendation system 4; the information input module comprises a display module 7 and a data transmission module 8, the data management module comprises a data updating unit 9 and a data calling unit 10, the medication auxiliary recommendation system comprises a gene combination prediction unit 5 and a drug and gene test unit 6, the database module is respectively connected with the display module, the data updating unit and the data calling unit, the data transmission module is connected with the gene combination prediction unit, and the gene combination prediction unit is connected with the drug gene test unit.
The database module stores gene data of various cancers and various subtypes and individualized prediction results of cancer driving genes and medicine combinations, and the data management module manages information stored in the database module. When diagnosis and treatment are carried out, firstly, cancer gene information and cancer subtypes of a patient are input into the system through the information input module, the data management module retrieves data of corresponding subtypes from the database module according to the input information, carries out medicine diagnosis and treatment prediction on the input genes according to the stored prediction results of the corresponding subtypes, carries out relocation and combined medication screening aiming at known medicines of individuals and provides an optimal diagnosis and treatment scheme. The invention firstly utilizes a big data analysis method to collect genomics data of various cancers and cancer subtypes, and then establishes a diagnosis and treatment effect model of the cancer driving gene and drug combination of each subtype to obtain the optimal drug combination with the best effect of treating the subtype. Inputting patient information, calling a diagnosis and treatment effect model of the subtype, predicting new indications of the medicines for individual patients from the optimal medicine combination, and simultaneously relocating known medicines and screening combined medicines.
As shown in fig. 2, the present embodiment is a method for genomic data management and diagnosis, which includes collecting cancer genomic data of various cancers, and establishing a cancer genomic database; constructing a sample space of a whole genome according to data in a database; constructing an individual accurate medication auxiliary recommendation system facing a patient by utilizing artificial intelligence and a bioinformatics algorithm based on genomics data; establishing a data management module for searching, inquiring and authority management control of genomics data; the information of the patient is input into the medication auxiliary recommendation system, and the medication auxiliary system performs combined medication screening according to the gene condition of the patient.
Individual data is collected for each cancer type, cancer subtypes are classified according to the cancer type and the tissue they control, and prediction of drug targets is then performed according to the specifically distinguished cancer subtype and the tissue it controls. The invention predicts the individuation of cancer driving genes and medicine combination by constructing an individualized accurate medication auxiliary recommendation system for cancer patients, further predicts the new anticancer indications of approved targeted drugs and small molecular drugs, and performs relocation and combined drug screening of known drugs. And a data management module is arranged, so that the safety of gene data is ensured.
The following further explains the technical scheme and technical effects of the present invention by specific contents.
The first step is as follows: taking liver cancer as an example, the method is oriented to liver cancer patients, collects cancer cell genomics data of the liver cancer patients, and establishes a genomics database covering common subtype of liver cancer.
The second step is that: constructing sample space of whole genome according to data in database
The sample space comprises the whole genome of a liver cancer patient and the whole genome of a normal cell, and the sample space of the normal cell is used as a control group, so that the prediction of individual liver cancer subtypes or drug targets of interaction between liver cancer genes and genes is facilitated.
The third step: based on genomics data, artificial intelligence and bioinformatics algorithm are utilized to construct patient-oriented individualized accurate medication auxiliary recommendation system
And classifying different liver cancer subtypes by utilizing a genetic classification algorithm through gene network analysis, and predicting drug targets according to the specifically distinguished liver cancer subtypes and tissues controlled by the liver cancer subtypes. And (3) constructing a prediction model of the combination of the liver cancer driving gene and the medicine, and finally constructing a liver cancer diagnosis and treatment prediction model by using a random forest algorithm.
The fourth step: and a data management module for searching, inquiring and authority management control of genomics data is established, so that the safety of the gene data is ensured.
The fifth step: inputting the information of the patient into a medication auxiliary recommendation system, and carrying out combined medication screening by the medication auxiliary system according to the gene condition of the patient
The liver cancer genomics information of a patient is input into a medication auxiliary recommendation system, then the cancer type is selected as liver cancer, a subtype is selected, a data management module updates a database, the medication auxiliary recommendation system carries out individualized diagnosis according to a common medication mode of the subtype, and the individual is subjected to prediction of anti-liver cancer new indications of targeted drugs and small molecular drugs, relocation of known drugs and combined medication screening.
The above-described embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention in any way, and other variations and modifications may be made without departing from the spirit of the invention as set forth in the claims.
Claims (9)
1. A genomics data management and diagnosis system, comprising:
information input module (1): for inputting cancer genomics data for a patient;
database module (2): storing genomic data of common subtypes of various cancers;
data management module (3): calling corresponding genomics data and a medicine combination prediction result according to the input patient information;
medication assistance recommendation system (4): according to the comparison between the called data and the patient data, the accurate medication assistance is carried out on the patient;
the medication assistance recommendation system (4) comprises:
gene combination prediction unit (5): predicting the individualization of cancer driver genes and drug combinations;
drug and gene assay unit (6): the method can predict new anticancer indications of targeted drugs and small molecule drugs, and can realize relocation and combined drug screening of known drugs.
2. The genomics data management and diagnosis and treatment system according to claim 1, wherein the information input module (1) comprises:
display module (7): the system is used for inputting patient identity information and displaying database information;
data transmission module (8): patient cancer genomics data is retrieved from the medical system based on the patient entered identity information.
3. The genomics data management and diagnosis and treatment system according to claim 1, wherein the data management module (3) comprises:
data update unit (9): updating genomics data in the database module in real time;
data call unit (10): and calling genomics data of corresponding subtypes in the database module according to the content of the information input module.
4. The genomics data management and diagnosis and treatment system according to claim 1, wherein the gene combination prediction unit (5) comprises a modeling module, and the modeling module is used for training a cancer diagnosis and treatment prediction model by using a cancer driver gene and a drug combination as inputs and using a corresponding treatment effect as an output.
5. A method for genomic data management and diagnosis using the system of any one of claims 1 to 4, comprising the steps of:
s1: collecting cancer genomics data of various cancers and establishing a cancer genomics database;
s2: constructing a sample space of a whole genome according to data in a database;
s3: constructing an individual accurate medication auxiliary recommendation system (4) facing a patient by utilizing artificial intelligence and a bioinformatics algorithm based on genomics data;
s4: establishing a data management module (3) for searching, inquiring and authority management control of genomics data;
s5: the information of the patient is input into a medication auxiliary recommendation system (4), and the medication auxiliary system performs combined medication screening according to the gene condition of the patient.
6. The genomic data management and diagnosis and treatment method according to claim 5, wherein the step S1 is further represented as: aiming at a certain cancer, the genomics of the cancer patient is collected from various large medical institutions, and a cancer genomics data group covering the common subtype of the cancer is established; and storing a plurality of cancer genomics data groups together to construct a cancer genomics database.
7. The method for genomic data management and diagnosis according to claim 5 or 6 wherein the sample space in step S2 includes the sample space of the whole genome of each cancer patient and the sample space of the whole genome of normal cells, and the sample space of normal cells is used as the control group.
8. The genomics data management and diagnosis and treatment method according to claim 5, wherein in step S3, the specific steps of constructing the patient-oriented individualized precision medication auxiliary recommendation system (4) by using artificial intelligence and bioinformatics algorithm are as follows:
s3.1: classifying different subtypes of the cancer by genetic classification algorithm through gene network analysis;
s3.2: predicting a drug target based on the differentiated cancer types and tissues controlled thereby;
s3.3: and constructing a cancer diagnosis and treatment prediction model by using a random forest algorithm.
9. The genomic data management and diagnosis and treatment method according to any one of claims 5 to 8 wherein the step S5 is further represented as: the cancer genomics information of a patient is input into a medication auxiliary recommendation system (4), then the cancer type and the subtype are selected, a data management module (3) updates a database, the medication auxiliary recommendation system (4) carries out individualized diagnosis according to the common medication mode of the subtype, and carries out prediction on new anticancer indications of targeted drugs and small molecular drugs and relocation and combined medication screening of the known drugs.
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